code: def set_env_on_import_paddle():
      if (
          "PADDLE_TRAINERS_NUM" in os.environ
          and "PADDLE_TRAINER_ID" in os.environ
          and "PADDLE_RANK_IN_NODE" in os.environ
      ):
          # 检测到了分布式环境的环境变量
          os.environ[FASTNLP_GLOBAL_RANK] = os.environ[
              "PADDLE_TRAINER_ID"
          ]
          # 如果不是由 fastnlp 启动的
          if FASTNLP_DISTRIBUTED_CHECK not in os.environ:
              os.environ[FASTNLP_BACKEND_LAUNCH] = "1"
  
file_path: fastNLP/fastNLP/envs/set_env_on_import.py
imports: import os
  import sys
  from .env import *
  import datetime
label_desc: Use image node_id 3 for calling a global function with example usage: set_env_on_import_paddle() without return types